The proposed continual neural mapping problem targets the updating of network parameters at each time when new observations arrive that lead to a self-improved mapping function. This problem setting falls into a continual learning [1]} category: the streaming data are no longer iid-sampled but highly correlated to adjacent ones. We want to update the mapping function in the newly observed areas while preserving an accurate mapping in previously visited regions without forgetting.
